exclude_random = function(d) {
d_overall_means = d %>%
group_by(modal, workerid) %>%
summarise(rating_m_overall = mean(rating))
d_indiv_means = d %>%
group_by(modal,percent_window, workerid) %>%
summarise(rating_m = mean(rating))
d_indiv_merged = merge(d_indiv_means, d_overall_means, by=c("workerid", "modal"))
cors = d_indiv_merged %>%
group_by(workerid) %>%
summarise(corr = cor(rating_m, rating_m_overall))
exclude = cors %>%
filter(corr > 0.75) %>%
.$workerid
print(paste("Excluded", length(exclude), "participants based on random responses."))
d = d %>% filter(!(workerid %in% exclude))
}
d1 = exclude_random(d1)
## [1] "Excluded 2 participants based on random responses."
d2 = exclude_random(d2)
## [1] "Excluded 1 participants based on random responses."
d3 = exclude_random(d3)
## [1] "Excluded 1 participants based on random responses."
d4 = exclude_random(d4)
## [1] "Excluded 4 participants based on random responses."
## Individual plots
plot(ps1$by_participant)
plot(ps2$by_participant)
plot(ps3$by_participant)
plot(ps4$by_participant)
So, we’re seeing what we expected for the confident speaker, with the AUC > in the optimistic condition than in the confident condition (indicating explaining away), but we’re not seeing the same (with just one speaker) for the pessimistic/cautious condition, where we would expect flipped results, with the pessimistic condition having a lower AUC than the cautious condition (with adaptation). To sum up, we expect the order to be, from greater to lower difference, “cautious”, “pessimistic”, “optimistic”, and “confident”.
##
## Two Sample t-test
##
## data: aucs.optimist$auc_diff and aucs.confident$auc_diff
## t = 0.72495, df = 13, p-value = 0.4813
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -12.60271 25.33260
## sample estimates:
## mean of x mean of y
## 9.637793 3.272847
##
## Two Sample t-test
##
## data: aucs.pessimist$auc_diff and aucs.cautious$auc_diff
## t = -1.1175, df = 12, p-value = 0.2857
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -52.78653 16.99633
## sample estimates:
## mean of x mean of y
## -2.021748 15.873352